Exploring Collaboration Patterns in GitHub Using Discrete Time Markov Chain

Collaboration among team members plays a crucial role in the success of software projects. GitHub has emerged as a prominent platform for collaborative software development. This study focuses on analyzing GitHub repositories to gain insights into project status and participant characteristics based on development activities such as commits and pull requests. Utilizing a discrete time Markov chain, this research models GitHub repositories and employs probabilistic temporal logic and model checking to shed light on the activity levels of both projects and participants. We expect that understanding these observed trends and patterns can assist project managers in strengthening teamwork and fostering productive collaboration.